Feature/named entity recognition

[ColinDaglish]

This PR adds a number of new features:

• extract feature count (i.e. word count by row) returns as a data frame
• total feature count (above summarised across all rows)
• named entity identification (extracts entity names like "ONS", "NHS" etc)

This also restructures the package, splitting out analysis functions and quality check functions from pre-processing functions.

Updated test suite to acompany new functions.

[codecov]

Codecov Report

Patch coverage: 57.35% and project coverage change: +4.71 🎉

Comparison is base (9a2fb6a) 64.57% compared to head (6a168c6) 69.28%.

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #11      +/-   ##
==========================================
+ Coverage   64.57%   69.28%   +4.71%     
==========================================
  Files           5        9       +4     
  Lines         223      394     +171     
==========================================
+ Hits          144      273     +129     
- Misses         79      121      +42     

Impacted Files	Coverage Δ
src/modules/visualisation.py	0.00% <0.00%> (ø)
src/run_pipeline.py	0.00% <0.00%> (ø)
src/modules/quality_checks.py	60.00% <60.00%> (ø)
src/modules/preprocessing.py	87.35% <75.00%> (ø)
src/modules/analysis.py	81.48% <81.48%> (ø)
tests/modules/test_analysis.py	87.75% <87.75%> (ø)
tests/modules/test_preprocessing.py	100.00% <100.00%> (ø)
tests/modules/test_quality_checks.py	100.00% <100.00%> (ø)

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[ColinDaglish]

@brenng1 I am ready for the next set of checks on this PR. I'm now going to start thinking about presentation, that is - how we are going to package this up into a report or something.